UROP Openings

Term:

Summer

Department:

20: Biological Engineering

Faculty Supervisor:

Alan Jasanoff

Faculty email:

jasanoff@mit.edu

Apply by:

2020-06-15

Contact:

horea@mit.edu

Project Description

Our lab combines the development of neurochemical biosensors with cutting-edge data analysis workflows. We are currently looking to extend the processing capabilities of a high-level preclinical magnetic resonance imaging (MRI) pipeline developed at the MIT as well as leading European universities. This provides a unique opportunity for a student to join the development of an innovative but reliable software framework, bearing ample possibilities for both learning and research.
The goal of this project is to extend the scope of data handling from our past focus on the mouse, to also include an organism with high relevance to neuroscientific and psychopharmacological research — the rat. As part of this project, you will be tutored in the technologies leveraged by the pipeline (including Git, Python, and Gentoo Linux), as well as in key concepts for efficient, transparent, and sustainable workflow design (including reproducibility, integration testing, dependency resolution, package management, and collaborative coding).
You will correspondingly be guided through the process of applying these skills in order to both develop and benchmark novel data processing capabilities. Your work will include programming in Python, using cutting-edge neuroimaging libraries such as nibabel and nipype, managing data resources, and ensuring that all resources can be used reproducibly.
## Research Context:
You can review the SAMRI package which you will be working on, on GitHub: https://github.com/IBT-FMI/SAMRI
The pipeline integrates with numerous peripheral acquisition and stimulation devices ( e.g. https://joss.theoj.org/papers/10.21105/joss.01171 ), and covers data repositing in a standardized format ( https://www.frontiersin.org/articles/10.3389/fninf.2020.00005 ), volumetric registration ( https://www.biorxiv.org/content/10.1101/619650v2 ), as well as statistical modelling and unsupervised classification.
As a short primer on preclinical MRI, you can watch the following video by one of the SAMRI authors, with whom you will be working: https://www.youtube.com/watch?v=ePamp9v5Z0U

Pre-requisites

To adequately tackle the challenges of this project you should:
* have some previous experience working on Linux.
* have some previous experience coding in Python.
* have a keen interest in software transparency and research reproducibility.
Though not mandatory or assumed, the following would be a significant plus:
* prior experience with the Gentoo Linux distribution
* prior experience with Git
* prior experience with MRI data